1. Field of the Invention
The present invention relates to microlithography, a key technology used in the manufacture of micro-electronic devices. Specifically the invention relates to optical proximity correction models, and more specifically, to methods for improving the through-process model calibration accuracy.
2. Description of Related Art
Feature sizes for microelectronics continue to decrease as processes and fabrication techniques become more sophisticated and accurate for small-scale designs. During projection microlithography, a pattern defined on a reticle is projected by a beam onto the surface of a suitable substrate such as a semiconductor wafer, exposing a photosensitive photoresist. The photoresist is then developed. Optical proximity effects act adversely on resolution. These effects are caused by the distortion of the light intensity distribution, which creates a difference in the size of the photoresist between a dense pattern area and an isolated pattern area, and generates occurrences of roundness or over-cutting of the edge of the pattern.
Optical proximity effects are known to cause deviations in the intensity profiles of shapes placed in different proximity environments, and generally occur in the range near the resolution limit. When employing a lithographic method, the photoresist response to the light intensity profile is nonlinear and introduces its own errors as well. The combination of the nonlinear optical response and nonlinear photoresist response creates image distortion. Other processes, such as photomask manufacturing and the etching of the photoresist pattern into films on the semiconductor wafer, may also contribute to the distortion of the image that is transferred onto the wafer, so that it no longer looks identical to the designed pattern.
The correction of these distortions by pre-distorting the design to compensate for the processing nonlinearities is typically called Optical Proximity Correction, OPC, even though several non-optical effects may also be addressed in this correction. OPC is facilitated through the use of a model, referred to as the OPC model, which emulates the patterning process. The OPC model is typically composed of an optical model and a photoresist model, although it is recognized that other processes such as photomask manufacturing and etching may also be included in the OPC model. The optical and photoresist models are calibrated by collecting scanning electron microscope (SEM) measurements of test patterns, and then utilizing statistical curve fitting algorithms to minimize the error between the measured data and the simulations of the test patterns using the model. The typical optical model is physically based with parameters that have direct correlation with physical phenomenon. On the other hand, photoresist models are typically empirical models made by fitting semi-arbitrary polynomials to measurement data. The fitting coefficients do not correlate directly to any physically measurable parameters.
When calibrating an OPC model, it is difficult to separate nonlinearities that occur due to the optics from those that occur due to the photoresist. Currently, there are no feasible methods for measuring the image intensity inside the photoresist, so that the effect of the optics cannot be directly measured. Additionally, since the intensity used to expose the photoresist is not known exactly, one cannot determine the exact response of the photoresist to the input intensity. The only information that is currently available to a practitioner in the art is the input to the optical system, for example the photomask, and the output of the resist processing in the form of SEM measurements. Both the optics and the photoresist contribute to the distortion, but without further information, it is not possible to separate each component. However, it is very desirable to be able to do so, since the control and reduction of the nonlinearities can only occur if the sources of those nonlinearities are well understood.
Two of the primary sources of process variation in a manufacturing lithography process, focus and dose control, are due to variations in the optical system, where the film stack that exists on the semiconductor wafer is considered part of the optical system due to its complex reflectivity. Focus and dose control contribute significantly to the image intensity profiles inside the photoresist. These parameters may be adjusted on a typical lithography exposure system so that the same photomask pattern may be imaged into a photoresist with the same optics, but using varying focus and dose values. The focus value from the exposure tool, referred to as the experimental focus, is considered the position where the optics creates the image with the best image fidelity. The combination of the focusing of the exposure system with the placement of the semiconductor wafer inside the exposure system results in a pattern transfer process with varying pattern fidelity. When this combination results in the best possible image fidelity, the focus condition is considered the experimental best focus. Likewise, the dose value from the exposure tool is a measurement of the total amount of light intensity projected into the photoresist. Since the photoresist responds to light intensity levels, changing the dose will cause the size of the photoresist pattern to change. The dose value that creates patterns in photoresist that are closest to the desired size is considered the experimental best dose.
Unlike optical parameters that can be varied freely during the exposure process, the photoresist response to the image intensity profile is considered to be a more stable phenomenon that can only be varied by changes in chemical formulation or changes in the photoresist processing. Some photoresist process variations, such as changes in post-exposure bake temperatures, can be varied more easily than changes in chemical formulation, but since the photoresist models are generally not physically based, they may not be independently calibrated. Many photoresist models are based on a Constant Threshold Resist (CTR) model, where the photoresist is assumed to respond in a binary fashion, such that the photoresist is exposed for all intensity levels above a certain threshold value and not exposed for all intensities below that value. The threshold value at which the photoresist is first exposed is called the printing threshold. In a CTR model, the multiplicative inverse of the printing threshold is exactly analogous to the exposure dose. Since the CTR model is generally not accurate for OPC or lithographic process window simulations, refinements of this model have been made in the form of a Variable Threshold Resist (VTR) model. These models are based on modeling the variation of the threshold as a function of image parameters, and some use the CTR threshold as a stable reference threshold at which to compute certain image parameters.
Other distortion mechanisms exist due to the interaction of the exposure tool and the photoresist, in addition to those due to global focus shifts or photoresist blurring effects. One example of distortion is the illumination source spectral bandwidth coupled with chromatic lens aberration, which introduces a blurring of the image due to different wavelengths of light being focused to slightly different planes. Other mechanisms include vibration of the wafer relative to the optics in a direction either in the plane of focus or perpendicular to that plane, and a tilting of the wafer or the exposure slit relative to the focal plane. These types of blurring mechanisms may sometimes be approximated by an equivalent defocus value, and attempts have been made to compensate for the effect of one mechanism through the control of another mechanism. At the present, these effects have been ignored in OPC models.
When calibrating an OPC model, it is desirable to use the correct values for any parameters that correspond to true physical effects. Since the optical model is physically based, there is the potential to use true focus and dose values in the model. However, this is usually not implemented because the experimental focus value depends on the placement of the semiconductor wafer in the exposure system. Consequently, the experimental value and the modeled or simulated focus value are not identical. Since the photoresist model is an empirical model that approximates the true physical response, the plane or planes at which the image intensity profile is computed does not correlate directly with the experimental focus value. Instead, for the typical photoresist model, the optical image is computed at one or more image planes and the photoresist model is applied to the computed image(s). If the image is computed at more than one plane, the intensity profiles at the different image planes are typically averaged. The photoresist model is applied to this average intensity profile. Moreover, the simulated process conditions may include thin films in addition to photoresist on the wafer, and the image may be calculated within one of these thin film materials as well. The simulated image is a function of both the simulated image plane and the simulated focus, and neither of these values is exactly the same as the experimental focus value.
The experimental dose value represents the total amount of light intensity that enters the exposure system and, although there should be a direct correlation of this value with the light intensity values that occur inside the photoresist, the experimental dose cannot be utilized as a parameter in the OPC model. The transmission of the light through the entire optical system, photomask and wafer film stack is not characterized well enough to know the intensity values exactly. Similarly with focus, the approximate nature of the photoresist model and the use of a single image intensity profile, either computed at a single plane or averaged over several planes, further confound the specification of a single physical dose value.
In an OPC model calibration procedure, the methodology generally requires collecting SEM measurements that represent the empirical data of the test patterns used in the model calibration. The test patterns are normally exposed at the nominal process conditions at which the manufacturing process is run. An initial estimate of the free parameters in the OPC model is then established, and a simulation of the pattern transfer process of those same test patterns is done. Using the simulated pattern transfer process and the empirical data, an error metric is computed between the simulated and empirical dimensions. The free parameters are then varied, the test patterns simulated a second time, and the error metric recomputed. This process is repeated until the minimum error metric is found using a particular set of the free parameters in the OPC model. Using this methodology, the image plane, focus position, and dose are considered free parameters and are set by minimizing the error between simulated and empirical data at nominal process conditions. Often, this minimization process is first carried out using only an optical model and a CTR model to predict the resist printing, and then repeated keeping the optical parameters fixed and optimizing the photoresist model parameters. Alternatively, both optical and photoresist parameters may be simultaneously optimized. Unfortunately, this alternative approach converges to an incorrect (not true) focus position.
In addition to their use in correcting for patterning non-uniformities through OPC, photolithographic simulations are used to aid in the development, optimization, and use of lithographic apparatus. The simulations may be helpful as a development tool, by quickly evaluating options, optimizing processes, and saving time by reducing the number of required experiments. Traditionally, simulations are used to define the best illumination conditions in terms of depth of focus, exposure latitude, or dose-to-size for printing a pattern onto a substrate. Exposure latitude is commonly defined as the percentage dose range where the printed pattern's critical dimension, CD, is acceptable, and depth of focus describes the range of optical focus values where the CD is acceptable. Dose-to-size refers to the dose that is necessary to print the pattern to the desired size. The depth of focus and the exposure latitude are used to determine the process window, which ultimately keeps the final photoresist CD within prescribed specification limits. To facilitate the simulation of lithographic process windows, accurate models of the optical image formation and photoresist response are required. These models may be equivalent to OPC models, although it is understood that often speed versus accuracy tradeoffs are made during lithographic simulation and these tradeoffs may lead to some models being more preferential for OPC applications, and others for lithographic process window simulation.
To ensure that the model properly predicts lithographic behavior in the presence of process variations, it is critical that the focus and dose values of the optical model be calibrated properly. This is not necessary for an OPC model that is only used at nominal process conditions. Consequently, OPC models have been developed without this criterion. It is desirable to use OPC models in an application requiring process window information. To do so, improved calibration methodologies are necessitated.